Data – what to do with it, where to put it? It’s been a conundrum for banks for years. Since the birth of the technological revolution, organisations have been gathering data at a rate of knots – personal customer data, purchasing behaviour, financial information – it’s all there, in big data centres, quietly ballooning in size.

But it’s only recently that rather than seeing it as a stream of consciousness, financial institutions have begun to realise it’s an important asset, which can be monetised.

So what exactly is data monetisation? It’s an umbrella term referring to the value organisations can extract from data, both in terms of revenue as well as brand value through differentiation.

It might be helping banks get an extra edge over the competition through selling smarter – finding out about customer buying patterns and then using that data to create cross sell or upsell opportunities, creating “stickiness” and increasing customer loyalty.

Data monetisation can also help them to spot when fraudulent activity is happening on an account – they can alert the customer and put a stop to it, helping the bank stem revenue leak. And they can use it externally, to help support digital advertising or for packaging data and selling it on to third parties, creating extra revenue that way.

Are banks doing it already? Sure they are. But it’s difficult. They face challenges. Take the legacy system issue. Most of our high street banks operate on a veritable spaghetti junction of systems.

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By GlobalData

Mortgage data might be stored on a mainframe in Southampton and corporate data in Scotland. It has been – until the advent of fintech – very difficult to create an organisation-wide view of data for many banks. Obviously challenger banks aren’t dogged with the same problem. But still, we wouldn’t say banks are the data monetization masters, not by a long stretch.

Let’s take a look at the early adopters, like the Chinese e-commerce behemoth, Alibaba, created by ex English teacher, Jack Ma. This summer it forecast its annual revenues would grow by between 45% to 49% adding $42.25bn to its value, largely down to its data goldmine.

The company’s services range from shopping and movies to finance and logistics, gathering up people’s spending, saving and viewing habits. Once that data is cleaned and sharpened up, it is sent back to the merchants who sell on the Alibaba platform, who then use it to better target their wares.

Analysts have called this a “potent marketing platform.” Alibaba also has a presence in the real world, so is able to combine online and physical data to get a 360-degree view of their customers. And it’s not just Alibaba. Tech giants like Google, Amazon and Facebook are also really well versed in data monetisation.

Will banks forever be on data monetisation catch up? Or will they eventually be able to play ball with the very profitable technology giants? They certainly aren’t taking it lying down.

Cloud take up has been significant in the financial services arena in the last few years, with banks, insurers and other institutions moving to cloud platforms. Using the cloud can help them circumvent any legacy system issues that might exist. The advent of open banking and the move towards open APIs (application program interfaces) and open source architecture is another big step in the right direction for the banks.

Open banking is based on the premise that customers want to view their banking information in non-traditional ways – they might want to view real time account balances when they’re using an e-commerce app, for example.

The basic premise is that customers have as many tools as possible with which to review or understand their finances. To do this, banks have to share customer data with third party companies or apps, securely and in real time.

Of course, for banks – and any other organisations headed down the data monetisation route – in addition to legacy systems, there are other obstacles that stand in the way. Poor quality data is always an issue, for example, which means banks have to be committed to continual data cleansing programmes. Data overload can also be a problem – there is so much data, identifying what is meaningful is tough.

But these are challenges that have to be – and will be – faced down. In this increasingly competitive landscape, where big data operatives like Google and Amazon are threatening to enter the fray, the ability to monetise data will spell success or failure.

Having the right data monetisation strategy in place and putting in the right combination of systems and processes that will help them deliver that strategy is vital. Data is an asset, their most valuable asset and the quicker they realise that, the better.

 

Augusto Negrillo is CEO of Certeco, a business technology change consultancy www.certeco.co.uk